Principal AI System Developer

Career Area:

Technology, Digital and Data

Job Description:

Your Work Shapes the World at Caterpillar Inc.

When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other.  We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.

Caterpillar is seeking an elite Principal AI System Developer to join our team and act as a champion of Artificial Intelligence (AI) and Advanced Analytics within Caterpillar’s Global Finance Services Division. Reporting directly to the Director of Advanced Analytics within Global Finance, you will lead the AI-enablement vision for our next-generation, enterprise-scale accounting data harmonizer system.

This is a critical senior AI engineering position requiring a rare blend of AI/LLM deployment expertise, robust software engineering experience with high-performance languages, and knowledge of modern cloud-native data architecture. Top candidates will also have experience with accounting systems and principles, and be able to collaborate across groups to understand, identify, and resolve all types of issues. You will lead the technical vision of an AI-enabled, resilient, and highly accurate system that serves as the backbone of enterprise-wide corporate accounting.

What You Will Do:

• IT Architecture Experience: Leverage previous experience in end-to-end architecture for a multi-sourced data platform, evaluating scalability, performance, and resilience. 
• AI-Driven Entity Resolution: Develop and implement sophisticated strategies for Entity Resolution (ER) by utilizing Large Language Models (LLMs) and Graph Databases (e.g., Neo4J, AWS Neptune, CosmosDB) to accurately map, reconcile, and standardize accounting data across diverse sources.
• Advanced RAG Implementation: Architect and deploy production-grade Retrieval-Augmented Generation (RAG) pipelines for complex data interpretation and standardization. This includes managing the underlying Vector Databases and optimizing prompt/context engineering for high accuracy.
• Performance Optimization: Understand performance SLAs. Leverage specialized databases such as OLAP solutions (e.g., DuckDB, ClickHouse) for rapid analytics and column stores/caching (e.g., Redis) for low-latency access.
• Cloud Infrastructure and Deployment: Engage with IT experts on cloud deployment strategy (AWS/Azure), containerization (Docker) and orchestration (Kubernetes) to ensure robust, scalable, and observable deployments.
• Cross-Functional Strategy: Collaborate directly with Accounting, ERP knowledge owners, IT, MDM, and Data Quality teams to translate complex accounting requirements into scalable, automated technical solutions.

Skills Descriptors:

Self-Starting, High Accountability, and Execution-Focused Mindset:

• Must demonstrate strong initiative, interpersonal skills, and the ability to communicate effectively

Core Engineering and Architecture:

• Programming Proficiency: Mastery in Python (for AI/ML) AND strong proficiency in at least one compiled, high-performance language (e.g., Go, Java, C#/.NET) for building scalable backend services
• Cloud Expertise: Extensive experience architecting solutions on AWS or Azure.
• Containerization & Orchestration: Knowledge of Docker and Kubernetes (K8s) in a production environment
• Streaming/Messaging: Proven experience designing systems utilizing Kafka or similar technologies (e.g., Kinesis, RabbitMQ)

Advanced AI/LLM Deployment:

• Demonstrated experience deploying LLMs in a production environment for data-centric tasks (not just chatbots)
• Specific expertise in building RAG pipelines, managing Vector Databases (e.g., Pinecone, Weaviate, PGVector), and advanced prompt/context engineering
• Experience with deep learning frameworks (PyTorch, TensorFlow) and the HuggingFace ecosystem
• Experience with Agentic Frameworks (e.g. LangGraph, AutoGen)

Modern Data Stack and Databases:

• Entity Resolution: Proven track record of solving complex entity resolution challenges at scale
• Graph Databases: Hands-on experience with Neo4J, AWS Neptune, or